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e included 289 in the accounted losses. In the end countriesdecided to focus on direct losses that are more easilymeasured, even though the importance of accounting forindirect losses at the national level was noted.Monitoring of progress towards proposed goals and targetswill require high quality loss data with a good temporal andspatial resolution, which is also important for DRR planning.Disaster loss accounting is considered a backbone forsetting baselines and for measuring progress towards settargets. However, compiling, maintaining and updatingdisaster data is challenging, and lack of clear standards anddefinitions has led to inconsistency and poorinteroperability of different data initiatives. While disasterloss data quality and coverage has significantly improved inrecent years, data gaps are common in many databases atall levels. There are gaps regarding: a) temporal coveragewith missing years and/or months; b) spatial coverage withmissing reports from some regions, communities, etc.; c)loss estimation with no losses reported for some events,particularly low impact/high frequency events; and d) lossindicators with inconsistent completeness across events 290 .At present there are three well-established globalmultihazard loss databases, Centre for Research on theEpidemiology of Disasters’s (CRED) EM-DAT, MunichRe’sNatCatSERVICE, and SwissRe’s Sigma (Table 4-2). While EM-DAT is an open database, the latter two are owned byinsurance companies and have limited public accessibility.The databases include reports provided by nationalgovernments, United Nations entities and otherinternational organisations or specialised national agenciesand NGOs, as well as newspaper sources. It has been noted,that information sources are fairly homogenous acrossdatabases and that reliability of the information rests withthe organisation in charge of publishing official figures 291 .This highlights the significance of data validation formonitoring purposes. Other databases with global orregional coverage do exist but they concentrate on one or ahandful of hazards, such as the United States GeologicSurvey’s database and Global Earthquake Model (GEM) 292for earthquakes 293 , and European PERILS 294 databasemainly for insured losses from windstorms.Table 4-2. Global multihazard loss databases 295Database Events covered since Threshold levels Variables coveredEM-DAT InternationalDisaster DatasetNatcat-SERVICE(MunichRe)1900 (about 21 000disasters)1980 (about 28 000disasters)casualties>10; numberaffected > 100; declarationof state of emergency; callfor international assistanceSome socioeconomicimpact; small-scale propertydamage or 1-9 fatalitiesSigma (SwissRe) 1970 (about 9 000 disasters) casualties > 20; injured >50; homeless > 2000; totallosses > USD 91.1 millionCasualties, affected (injured, homeless,affected), estimated damageInsured losses; total losses; injured;infrastructure areas and industries affectedCasualties; missing; injured; homeless; insuredlosses (claims); total lossesNational loss databases do exist but to date these have notusually followed a common methodology in their datacollection, limiting their usability for monitoring andparticularly research and planning. However, a UN-ledeffort to standardise methods and criteria for disaster lossaccounting, originally set up by an academic network in1994 in Latin America, has developed into a promising basisfor the future. Based on the DesInventar 296 methodology,85 countries and territories have now published nationalloss data and many more are in the process of establishinglinking databases. The European Commission recentlyincluded the common methodology used for thesedatabases in its guidelines for disaster loss accounting inEurope and beyond 297298 . While not all countries currentlyhave national disaster loss databases, the adoption of boththe SDGs and the Sendai Framework targets for DRR willrepresent a strong incentive for systematically recordingloss data.Role of jointly used methodologies and definitionsSignificant efforts have been undertaken to improve theinteroperability of disaster loss data from national andglobal databases through the development of commondata standards and methodologies, but much work remainsto be done. An overview of the current practices in EUcountries at national level showed that the methodologiesfor loss data recording are appropriate for nationalpurposes, but to make the databases compatible withinEurope and with international organisations they all wouldrequire adjustments 299 . Another analysis 300 noted thatnational loss databases are not consistently available across75